Robust and Highly Secured Palm Print Identification System for Biometric Authentication
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Abstract
For securing personal identifications and highly secure identification problems, biometric
technologies will provide higher security with improved accuracy. This has become an emerging
technology in recent years due to the transaction frauds, security breaches and personal identification
etc. The beauty of biometric technology is it provides a unique code for each person and it can’t be
copied or forged by others. These systemsare getting wide acceptance in the networked society,
replacing passwords and keys due to its reliability, uniqueness and the ever increasing in security
demand. Generally, we have finger print Biometric systems in now a days, but there are many chances
to copy one’s finger prints without knowing him. There by, we can make a forgery to authorize his
personal accounts, computers and even drawing cash form ATM’s etc. To overcome the draw backs
of finger print identification systems, here in this paper we proposed a palm print based personal
identification system, which is a most promising and emerging research area in biometric
identification systems due to its uniqueness, scalability, faster execution speed and large area for
extracting the features. It provides higher securityover finger print biometric systems with itsrich
features like wrinkles, continuous ridges, principal lines, minutiae points, and singular points. The
main aim of proposed palm print identification system is to implement a system with higher accuracy
and increased speed in identifying the palm prints of several users. Here, in this we presented a highly
secured palm print identification system with extraction of region of interest (ROI)with morphological
operation there by applying un-decimated bi-orthogonal wavelet (UDBW) transform to extract the
low level features of registered palm prints to calculate its feature vectors (FV) then after the
comparison is done by measuring the distance between registered palm feature vector and testing
palm print feature vector. Simulation results show that the proposed biometric identification system
provides more accuracy and reliable recognition rate.
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